Social spiders and hilarious field equipment

Before I even explain the topic of today’s post, I have to tell you that the papers that I’m blogging about today use the best and most hilarious piece of field equipment that I have ever seen. Project budgets may never be the same. I may even need to change study systems. Read on, if you dare.

The literature on parasites and animal personalities is ever-growing, perhaps because personalities have palpable consequences for transmission dynamics: the likelihood of direct transmission between infected and susceptible hosts often depends on host behavioral tendencies and their impacts on social interactions. I’ve blogged about this in the past: aggressive Tasmanian devils are more likely to transmit facial tumor disease to non-aggressive conspecifics and house finches that dominate the use of artificial feeders are more likely to acquire and transmit conjunctivitis. Similarly, in a world (er, Africa) where spiders live together in a shared web and cooperatively capture and share prey, bold spiders are more likely to transmit cuticular bacteria to shy spiders than shy spiders are to bold spiders (Keiser et al. 2016a). And what’s more, spider social networks are behaviorally disassortative, where bold spiders were more likely to rest in contact with shy spiders than they are with their own personality types. Thus, it appears that this system might be poised for rapid transmission of microbes, depending on the personality composition of the susceptible spiders in the colony.

These South African social spiders (Stegodyphus dumicola) live in colonies of a few dozen to over a thousand individuals. The ability to capture a large amount of large prey items is key to a colonies’ success, and colonies attack faster when they contain a mixture of bold and shy personality types in the group (Keiser et al. 2014). Furthermore, the execution of this important collective behavior is often based on the behaviors of one or a few important “keystone individuals” or leader spiders (Pruitt & Keiser 2014). These keystone individuals are so important in this system – and probably in many other systems, too – that we have to wonder: what happens when the keystone individuals take a sick day or even die from infection?

It turns out that increased bacterial load on colonies’ keystone individuals can impair the collective behavior of their entire society (Keiser et al. 2016b). Specifically, groups whose keystone individual are exposed to bacteria attack prey stimuli more slowly, and fewer individuals participate in the attack. Interestingly, the keystone’s participation in the task is not altered, suggesting that increased bacterial load alters the way keystones influence their colony-mates’ behavior.

Perhaps you find yourself wondering how, exactly, one might measure a spider group’s response to prey stimuli. Do you sit around and wait all night for some prey to get caught in the web? Boring. Do you try to throw a moth into the web and watch what happens? Rude. No, what you do is you attach a “hand-held vibrator” (Model: Flamenco Purple no. 4, Golden Triangle; do not Google if you’re at work) to a wire and then attach a piece of paper to the other end of that wire, and you use that vibrating piece of paper as your simulated prey. This is brilliant, and I HAVE SO MANY QUESTIONS. Why that model? How awkward is international travel for field work? I must know!

Anyways, social spiders are awesome, their personalities influence pathogen transmission, and their pathogens influence the role that individuals’ personalities play in colony behavior. Cool stuff!

References:

Keiser, C.N., Jones, D.K., Modlmeier, A.P. & Pruitt, J.N. (2014) Exploring the effects of individual traits and within-colony variation on task differentiation and collective behavior in a desert social spider. Behavioral Ecology and Sociobiology, 68, 839-850.

Keiser, C.N., Pinter-Wollman, N., Agustine, D.A., Ziemba, M.J., LingranHao, J.G.L., and Pruitt, J.N. (2016a). Individual differences in boldness influence patterns of social interactions and the transmission of cuticular bacteria among group-mates. Proceedings of the Royal Society B, 283, 20160457.

Keiser, C.N., Wright, C.M. & Pruitt, J.N. (2016b) Increased bacterial load can reduce or negate the effects of keystone individuals on group collective behaviour. Animal Behaviour, 114, 211-218.

Pruitt, J.N. & Keiser, C.N. (2014) The personality types of key catalytic individuals shape colonies’ collective behaviour and success. Animal Behaviour, 93, 87-95.

Is zombie transmission transmission frequency or density dependent?

For reasons that I cannot explain, visitors have started to stumble upon my blog by googling the question, “is zombie infection frequency or density dependent?” Maybe there’s a really awesome educator out there using that example in class. Or maybe the zombie apocalypse has started and people are secretly beginning to plan for the end. Either way, this is a neat question that I’m willing to speculate about!

First, we need to decide what kinds of zombies we are talking about. Let’s assume we’re looking at World War Z type zombies, where infection is transmitted via bites/saliva/fluid transfer. Let’s say that the zombies are highly mobile and thus the human and zombie populations are well-mixed. Also, let’s assume that zombies don’t really have a contact structure, like humans do, because they’ve lost any kind of social system that they had a humans.

Given those assumptions, I would expect disease-relevant contacts to increase with host density. So, if I had to pick between density dependent and frequency dependent transmission, I’d expect density dependent transmission. But don’t forget that there are nonlinear contact functions, too. Those might work better, because even a tireless biting machine can only bite so many people per day.

When might zombie transmission be frequency dependent? FD transmission would be appropriate if larger populations covered larger areas, so that host density was constant. I suppose that could happen if humans were dispersing as much as possible and running away from zombie-packed areas. What do you think?

Contex-dependent symbiont dispersal: my favorite symbiont ecology paper of 2015!

For symbionts, transmission is dispersal. When free-living species (e.g., lions, aphids, and ducks) disperse, we expect them to have dispersal strategies that have been favored by natural selection; they should leave habitats where fitness prospects are low and preferentially disperse to habitats where fitness prospects are high, as long as the fitness benefits outweigh the costs. Logically, symbionts should also move from low quality to high quality habitats, where the “habitats” are hosts or locations on the host. However, we almost always assume that symbiont transmission/dispersal is a random process with a fixed rate. That is, we assume that host quality or site quality on the host doesn’t matter. But guess what? IT DOES MATTER. And you can read all about it in my favorite symbiont ecology paper from 2015! I’ll summarize it for you here:

The branchiobdellidan-crayfish symbiosis is one of my favorite symbiont-host systems, so I’ve blogged about it several times previously (e.g., here and here). In contrast to the Chaetogaster-snail system that I talked about last week, it’s relatively easy to measure branchiobdellidan fitness, because the branchiobdellidans lay cocoons on their crayfish hosts. Adult branchiobdellidans stay nearby and tend their little cocoon gardens (adorable!), so it’s easy to quantify each worm’s reproductive output.

In a field survey of branchiobdellidans on crayfish, Skelton et al. (2015) found that branchiobdellidan reproduction depended on crayfish size and the microhabitat on the host; some microhabitats favored branchiobdellidan reproduction, while cocoons were never found in other microhabitats. Also, there was a limit to the number of worms found in any given microhabitat, where some microhabitats on the crayfish could support more worms than others. And here’s something even more awesome: branchiobdellidans weren’t found in the suboptimal microhabitats unless the better microhabitats were already full. Ideal free distribution, anyone? SO. COOL.

But it gets better. Using the field survey data, Skelton et al. (2015) built a symbiont fitness-based dispersal model that incorporated crayfish size and microhabitat occupancy and quality, where there was some fitness threshold below which worms would disperse from donor to receiver crayfish. Then they ran a lab experiment where they put donor crayfish (with worms) in tanks with receiver crayfish (without worms), and counted how many worms dispersed and where on the hosts the worms ended up. Skelton et al. (2015) didn’t know what the worm fitness threshold was, so they used a model fitting procedure to figure out which threshold produced the best fits to the experimental data. The resulting fitness-based dispersal model could predict whether worms would disperse with 95% accuracy. 95% ACCURACY!! And 67% of the time, the model predicted the exact number of worms that dispersed. In contrast, the model that assumed a fixed rate of dispersal – with no influence of host size or microhabitat occupancy – couldn’t predict dispersal any better than a null model. When’s the last time an ecologist predicted something with 95% accuracy?!

So, symbiont dispersal not only depends on symbiont fitness prospects, but knowing which factors influence symbiont fitness can allow us to predict symbiont transmission/dispersal with incredible accuracy – much better than if we assumed a fixed rate. This has huge implications for the way that we model symbiont transmission! Go check out the paper. It’s beautiful.

References:

Skelton, J., R.P. Creed, and B.L. Brown. 2015.  A symbiont’s dispersal strategy: condition-dependent dispersal underlies predictable variation in direct transmission among hosts. Proceedings of the Royal Society B 282: 20152081.

Context dependent symbiont transmission: Part I

If ever there was a “law” in parasite ecology, it would be that macroparasites are aggregately distributed among their hosts. For instance, when Shaw and Dobson (1995) surveyed the literature, they found that 268 out of 269 macroparasite distributions were overdispersed/aggregated, so that a minority of the hosts harbored the majority of the parasites. The other options – which were not observed – were that parasites would be randomly or uniformly distributed among their hosts.

Previously, we’ve discussed some of the mechanisms that can lead to aggregation of macroparasites. Most of these mechanisms fall under a big umbrella that we can label “variation in transmission rates among hosts causes parasite aggregation.” Additionally, aggregation can occur if parasites reproduce directly on the host and the “offspring” do not all leave the host. That isn’t a typical characteristic of a macroparasite life cycle, but it is a possibility. So, we have direct reproduction and variation in transmission rates pushing macroparasite distributions away from random distributions and towards aggregated distributions (Anderson and Gordon 1982).

I should also point out that there are mechanisms working in the opposite direction to push parasite distributions from overdispersed or random distributions to more uniform or underdispersed distributions. These are density-dependent processes, such as density dependent parasite mortality, density dependent parasite transmission/emigration, and infection intensity dependent host mortality (Anderson and Gordon 1982).

To illustrate these ideas, let’s take a look at a real system. Enter Chaetogaster limnaei, an oligochaete worm that lives on the headfoot and in the mantel cavity of freshwater snails. It is unclear whether Chaetogaster is a parasite, a commensal, or a mutualist of snails. Like many symbionts, it may be that the net outcome of the symbiont-host relationship is context-dependent. But for our purposes, let’s use the term “macroparasite” when referring to Chaetogaster, because we know that these oligochaetes share an important trait with macroparasites: the oligochaetes are aggregately distributed among snail hosts (Hopkins et al. 2013). However, unlike many macroparasites, Chaetogaster reproduce directly on the host and the “offspring” do not all immediately leave the host, so Chaetogaster may be aggregated for that reason alone. But are there other processes affecting Chaetogaster distributions?

First, let’s ask whether there are any density-dependent processes that might favor random or underdispersed Chaetogaster distributions. As far as we know, the oligochaetes do not kill their typical snail hosts at any densities, so infection intensity dependent host mortality is probably not a prominent process. We also don’t know much about density-dependent parasite mortality, though the oligochaetes may have higher mortality rates at high density (Hopkins et al. 2013). Finally, Chaetogaster dispersal rates to new hosts do not appear to be influenced by Chaetogaster density, so transmission isn’t density dependent (Hopkins et al. 2015).

Before we talk about variation in Chaetogaster transmission rates, we need to discuss how Chaetogaster are transmitted, because it was previously unclear whether Chaetogaster could leave one host to disperse to another host without host contact. Hopkins et al. (2015) made tiny little leashes for snails and tethered pairs of snails so that they could or could not touch. When the snails could touch, Chaetogaster dispersed among the snails until they reached a roughly 50/50 distribution. But when the snails could not touch, Chaetogaster wouldn’t disperse. Therefore, Chaetogaster are directly transmitted…unless the snail that starts with the Chaetogaster is euthanized, in which case the Chaetogaster readily jumped ship.

In a series of subsequent experiments, Hopkins et al. (2015) showed that the roughly 50/50 Chaetogaster distribution among snail hosts only occurred when the two snails were similar. If the snails were different sizes, more Chaetogaster would disperse from large to small snails than from small to large snails. There was also variation in Chaetogaster dispersal/transmission rates depending on whether the donor or receiver snails were infected and shedding trematode cercariae – a major food source for Chaetogaster. So there was variation in Chaetogaster transmission rates, which could help explain why Chaetogaster are aggregated among snail hosts!

But why did Chaetogaster transmission rates vary with host characteristics? It is probably related to Chaetogaster fitness on hosts with different characteristics, where Chaetogaster are more likely to disperse from hosts where Chaetogaster fitness is low. However, it’s hard to measure Chaetogaster fitness, because the worms reproduce asexually. Next week, I’ll tell you about my favorite paper from 2015, which quantified fitness-based symbiont dispersal in a different system. Stay tuned!!

References:

Anderson R, Gordon D (1982) Processes influencing the distribution of parasite numbers within host populations with special emphasis on parasite-induced host mortalities. Parasitology 85:373–398.

Hopkins SR, Wyderko JA, Sheehy RR, Belden LK, Wojdak JM (2013) Parasite predators exhibit a rapid numerical response to increased parasite abundance and reduce transmission to hosts. Ecol Evol 3:4427–4438.

Hopkins SR, Boyle LJ, Sheehy RR, Belden LK, Wojdak JM (2015) Dispersal of a defensive symbiont depends on contact between hosts, host health, and host size. Oecologia 179(2):307-18.

Do you REALLY know how parasites are transmitted in your system?

Observing transmission events – and knowing that you just observed a transmission event – can be really tricky, but it’s a really important step in understanding parasite ecology in any given system. For instance, last week I talked about the Mg pathogen that causes conjunctivitis in house finches, and I told you that the pathogen might be transmitted among birds via bird feeders (=fomites). This possibility is corroborated by evidence that the number of direct contacts made by individual birds didn’t influence the probability of infection; that is, bird feeders seem more plausible than bird-bird contacts. But it’s still hard to say that Mg is never transmitted by direct contacts between birds, or how often that kind of transmission might occur. And that’s in a system where they’ve really spent a lot of time figuring out how the pathogen is transmitted!

Another good example is of this uncertainty in transmission routes comes from gastrointestinal pathogens. Pathogens that cause all kinds of diarrhea seem to be utilizing a strategy where they get out there and contaminate the environment and thereby make contact with other potential hosts. Based on that idea, we usually assume that fecal-oral transmission is really important to gastrointenstinal pathogens, whereas direct contacts among hosts are less important. Is that really true?

In a recent study, Blyton et al. (2014) quantified how long pairs of possums hung out at night, whether they were pair-bonded (=sex presumably happened), whether they shared dens during the day, and how much spatial overlap they had in their ranges. They related those potential drivers of transmission to the probability that the possums shared strains of non-pathogenic E. coli. Surprisingly, spatial proximity wasn’t important to strain-sharing, but the total time that pairs spent interacting was important, which is counter intuitive for transmission based on environmental contamination. But Blyton et al. (2014) posit that the most important kinds of contacts were brief nocturnal associations, rather than all-day den sharing or long-term pair-bonding. That’s seems really crazy, until you remember that possums probably aren’t defecating in their dens. It might be that the brief nocturnal associations are likely to result in contact with fresh, contaminated poo and E. coli transmission than den-sharing or simply living near an “infected” possum. Neat! But notably, we still don’t know exactly how E. coli is being transmitted in that system!

Anyone have any other notable examples of pathogens whose transmission routes we haven’t totally figured out yet? Here are two examples from systems with vector-based transmission:

What is the predominant transmission route by which prairie dogs contract the plague?

What was the predominant transmission route by which humans contracted the Bubonic plague?

Reference:

Blyton, M.D.J., S.C. Banks, R. Peakall, D.B. Lindenmayer, and D.M. Gordon. 2014. Not all types of host contacts are equal when it comes to E. coli transmission. Ecology Letters 17: 970–978

Are superspreaders also superreceivers?

For simplicity, we often assume that all hosts have an equal probability of becoming infected by and transmitting parasites and pathogens. But of course, we know that it isn’t how real systems work. For instance, in real systems, hosts vary in their propensity to become infected by pathogens, and that variation is one probable cause of the parasite ecology “law” that macroparasites are aggregately distributed among hosts. We call hosts that are highly susceptible to a given pathogen “superreceivers,” and hosts that are highly likely to transmit a pathogen are “superspreaders.”

Here’s a question for you to ponder: are superspreaders usually superreceivers and/or are superreceivers usually superspreaders? For instance, sex workers are at high risk for contracting HIV (=superreceivers) because they frequently change sex partners, and they’re also highly likely to spread HIV (=superspreader), if they have it, in comparison to the average person. In that case, the superreceivers are also superspreaders. When that happens, we might predict really explosive epidemics whenever “patient zero” is a superreceiver+superspreader, because R0 will be very, very high.

But consider the Tasmanian devil example that I posted about recently. Tasmanian devils that bite lots of individuals are highly likely to contract Tasmanian devil facial tumor disease; they’re superreceivers. But being bitten by an infected individual doesn’t seem to transmit the infectious cancer to the receiving host, so devils that bite frequently don’t transmit any more frequently than devils that don’t bite frequently. Therefore, the superreceivers in that system aren’t superspreaders.

Now let’s talk about a really cool system that I somehow haven’t blogged about yet. House finches are hosts for an emerging bacterial pathogen (Mycoplasma gallisepticum – Mg) that jumped from poultry into house finches in the 1990s. This pathogen causes conjunctivitis in the house finches – a symptom you don’t often think about in wildlife! In a really neat recent paper, Adelman et al. (2015) showed that birds that spent more time on bird feeders were more likely to become infected by (superreceivers) and transmit (superspreaders) Mg. This is a really cool example of a pathogen that appears to be transmitted by “fomites”: inanimate objects that the pathogen can survive on when off the host.

We probably don’t have enough examples in the literature to determine whether superspreaders are usually superreceivers or to look for generalities in systems where this occurs. But we’re accumulating more examples all the time! Stay tuned.

…if academics were at higher risk of developing conjunctivitis when they sought out free food, I’d have some very squinty-eyed colleagues.

Reference:

Adelman, J.S., S.C. Moyers, D.R. Farine, and D.M. Hawley. 2015. Feeder use predicts both acquisition and transmission of a contagious pathogen in a North American songbird. Proc Biol Sci. 282(1815): 20151429.

Inferring intra and interspecific parasite transmission from parasite population genetic structure

It’s often important to know how frequently parasites are transmitted among hosts of the same species (intraspecific transmission) or among hosts of different species (interspecific transmission). But observing parasite transmission events can be very difficult in wildlife populations, so we often have to use proxies instead of measuring transmission rates directly. For instance, we might use the frequency with which two bird species share a nesting site as a proxy for how frequently we think that transmission should happen between the two species.

But of course, transmission doesn’t necessarily happen when two species contact each other. So how can we determine whether interspecific transmission is really happening? There’s more than one method, but today, I just want to talk about a cool method that I’ve seen in a bunch of recent papers: comparisons of parasite population genetic structure within and among host species. If parasite populations are highly genetically differentiated among host populations or among host species (or even among individual hosts!), then there is evidence for low parasite transmission and thus genetic mixing among host populations or among host species (or individual hosts). Conversely, if there is no genetic differentiation in parasite populations among host populations or host species, then there may be high parasite transmission among host populations or host species. Here are a whole bunch of examples of how this idea has been explored in the literature recently:

Ectoparasitic flies on bats (Olival et al. 2013):

Olival et al. (2013) sampled bat flies on three species of bats in the Pteropus genus at eight sites in Malaysia, Cambodia, and Vietnam. Almost all of the bat flies were from a single species: Cyclopodia horsfieldi. An analysis of the molecular variance in the sampled bat flies showed that very little of the variation was explained by geographic region or host species. This suggests high rates of interspecific transmission of this bat fly species among the three Pteropus bat species. Previously, interactions between the three bat species, including roost sharing, were thought to be uncommon. But because the bat flies pupate off the host in the roosts, Olival et al. (2013) suggest that perhaps interspecific transmission can happen when the different bat species share the same roost locations sequentially, rather than at the same time.

Even though there was low genetic structuring in the sampled Cyclopodia horsfieldi bat flies, for one bat host species (Pteropus hypomelanus), there was relatively low gene flow in the parasite population at some isolated island sites. It turns out that bat gene flow is also low at those smaller, more isolated island sites. But if that’s the case, then why don’t those parasites have distinctly different genetic lineages from other sites and host species?  Olival et al. (2013) suggest that one of the bat species, Pteropus vampyrus, visits those more isolated island populations of Pteropus hypomelanus during long-distance dispersal, and that those visits provide enough population mixing to prevent divergence in the parasite lineages among sites and host species.

Ectoparasitic mites on bats (van Schaik et al. 2014):

Let’s stick with bats, but shift our geographic focus to central Europe and our parasite focus to mites in the genus Spinturnix. S. myoti mites live on Myotis myotis bats and S. bechsteini mites live on Myotis bechsteinii bats. Both mites have similar life histories, and they are only transmitted during direct contact; they can only survive for a few hours off a host bat, unlike the bat flies discussed above. S. myoti mites had high genetic diversity and panmictic genetic structure, with no differentiation among bat populations. S. bechsteini mites had low genetic diversity and high differentiation among bat populations. van Schaik et al. (2014) suggest that the differences in the genetic structure of the two mite species can be explained by the differences in the social systems of the two bat species. Myotis myotis bats have larger colony sizes, more inter-colony visits during the maternal season, and closer intraspecific associations during the mating season, and all of these factors could lead to more intraspecific transmission of S. myoti mites, both within and among colonies. That is so cool! (By the way, check out this post for more information about the relationship between host contacts and parasite transmission.)

Ectoparasitic flies on birds (Levin and Parker 2013):

In the Galapagos, great frigatebirds (Fregata minor) are parasitized by Olfersia spinifera hippoboscid flies, and Nazca boobies (Sula granti) are parasitized by Olfersia aenescens hippoboscid flies. The great frigatebirds have distinct genetic population structure among islands, but their hippoboscid flies and a pathogen transmitted by the flies (Haemoproteus iwa) have no genetic differentiation among islands (Levin and Parker 2013). Also, of the few Olfersia spinifera hippoboscid flies sampled on a second frigate species (F. magnificens), all flies had the most common fly haplotype on great frigatebirds. Similarly, the Nazca boobies had distinct genetic lineages among sites, whereas the hippoboscid flies on boobies showed no genetic differentiation among sites or among multiple booby host species.

So, what’s going on? How could the parasites be so well-mixed among sites, while their bird hosts are not? Levin and Parker (2013) suggest two hypotheses: 1) maybe alternative host species that weren’t considered in this study are doing lots of island hoping and carrying flies around with them. Remember that Pteropus vampyrus bats may play that kind of role in the bat fly example above. 2) Host genetic structure is distinct among islands because the birds are philopatric; they like to mate at their natal breeding site. But juvenile birds may still visit other sites without mating, and thus without influencing bird population genetic structures, and those visits could spread the parasites among the islands, thus mixing the parasite lineages.

Feather lice on birds (Koop et al. 2014):

Let’s stick with birds in the Galapagos, but let’s change our focal host to hawks (Buteo galapagoensis) and our focal parasites to feather lice (Degeeriella regalis). Hawks are thought to cross open water far less often than the frigatebirds and boobies in the previous example. Unsurprisingly, Galapagos hawk populations have high genetic differentiation among islands, where the genetic differences among populations increase with the distance among islands (Koop et al. 2014). Hawk feather lice also show high genetic differentiation among islands, unlike in our previous parasite examples. This suggests that there is very little interpopulation dispersal of lice, and there isn’t an alternative host carrying lice to different islands, either. Furthermore, lice are mostly vertically transmitted from parent to offspring, rather than the host-roost-host or horizontal host-host transmission routes in the previous systems. As a result, there is also genetic differentiation of lice among individual hosts, so that each host acts like a parasite island! Neat!

Feather mites on birds (Dabert et al. 2015):

Birds again, but now let’s talk about feather mites on two species of skuas (arctic and long-tailed skuas) in Svalbard. The mites are thought to be transmitted only during direct host contact, either vertically from mother to offspring or horizontally among hosts. Even though the two skua species nest at the same sites during the breeding season, nests tend to be spaced far apart, so Dabert et al. (2015) predicted that the two skua species would have distinct mite species. Both skua species had mites in the Alloptes genus, which were morphologically very similar, but which were genetically distinct enough between the two host species to be classified as two different species. However, both skua species also had Zachvatkinia isolata mites, and those mites had a well-mixed population with no evidence for genetic differentiation among host species. How could that be? Well, the two skua species do contact each other, during very brief but common aerial fights. And it may be that Zachvatkinia isolata mites, which are more abundant on the host and specialize on a relatively external region of the feathers, are more likely to be transmitted during those brief aggressive encounters than the Alloptes mites that hang out in more protected parts of the plumage. UHM, AWESOME.

You might be wondering if similar studies have been done with host species that don’t fly, or with endoparasites instead of ectoparasites. There is some endoparasite work, like with schistosomes and whipworms, but I’m not going to cover it here. As for non-flying host species, check back next week for an example of how the insight gained from studies like this can be used in an applied way to manage parasite transmission.

(I was watching a lot of Fringe when I made this cartoon.)

References:

Dabert, M, SJ Coulson, DJ Gwaizdowicz, B Moe, SA Hanssen, EM Biersma, HE Pilskog, and J Dabert. 2015. Differences in speciation progress in feather mites (Analgoidea) inhabiting the same host: the case of Zachvatkinia and Alloptes living on arctic and longtailed skuas. Exp Appl Acarol 65:163–179.

Olival, KJ, CW Dick, NB Simmons, JC Morales, DJ Melnick, and K. Dittmar. 2013. Lack of population genetic structure and host specificity in the bat fly, Cyclopodia horsfieldi, across species of Pteropus bats in Southeast Asia. Parasites & Vectors 6:231

Koop, JA, KE DeMatteo, PG Parker, and NK Whiteman. 2014. Birds are islands for parasites. Biology Letters 10: 20140255.

Levin, II, and PG Parker. 2013. Comparative host–parasite population genetic structures: obligate fly ectoparasites on Galapagos seabirds. Parasitology 140: 1061–1069.

van Schaik, J, G Kerth, N Bruyndonckx, and P Christe. 2014. The effect of host social system on parasite population genetic structure: comparative population genetics of two ectoparasitic mites and their bat hosts BMC Evolutionary Biology 14:18.

Parasite transmission: density-dependent, frequency-dependent, or neither?

A few months ago, I blogged about the difference between density-dependent (DD) and frequency-dependent (FD) transmission.  To recap, the difference is all about the shape of the contact rate function with regards to host density: in FD transmission, contact rate is assumed to be independent of host density.  In DD transmission, contact rate is assumed to linearly increase with host density.

So, do we really only get two options?  A linear increase or no relationship?  As it turns out, there are a whole bunch of proposed transmission equations in the literature where contact rates are not linear or constant (e.g., McCallum et al. 2001).  In fact, many authors have suggested that neither DD nor FD transmission are appropriate models; instead, the contact rate function (as measured by the transmission rate function) falls somewhere between the two, increasing non-linearly with host density (e.g., Fenton et al. 2002). The theoretical argument for a non-linear contact rate function is similar to the argument for using a Holling Type II functional response instead of a Holling Type I functional response for predator-prey interactions: a linear contact rate function might make sense at some host densities, but could contact rate really just keep increasing infinitely with host population density?  Or should we expect saturation of contact rates at high host densities, where eventually adding another 100 or 1,000 hosts doesn’t appreciably change the per capita contact rate?

Most of the work in this area is from mathematical models/simulations, because it can be hard to measure animal contact rates (even when scientists get creative and use mouse raves and painted lice).  We need more empirical data!!!  This recent Ecology paper by Cross et al. (2013) is a good start.  They quantified contact rates among female elk around Yellowstone using proximity logger collars, and found that contact rates increased non-linearly with group size, which they were kind of using as a proxy for density.

Given that the shape of the contact rate function is a fundamental assumption of every epidemiological model, I think there is shockingly little evidence to support the use of DD, FD, or non-linear transmission.  MORE DATA, PLEASE.

References:

Cross, P., T. Creech, M. Ebinger, and K. Manlove. 2013. Female elk contacts are neither frequency nor density dependent. Ecology 94:2076–2086.

Fenton, A., J. Fairbairn, R. Norman, and P. J. Hudson. 2002. Parasite transmission: reconciling theory and reality. Journal of Animal Ecology 71: 893–905.  (PDF link)

McCallum, H., N. Barlow, and J. Hone. 2001. How should pathogen transmission be modelled? Trends in Ecology & Evolution 16: 295–300. (PDF link)

Parasites, Spatially Structured Populations, and the Evolution of Virulence

In the past few weeks, I’ve spent a lot of time thinking about how spatial heterogeneity and spatially structured host populations affect parasite transmission.  Consider this post my brain dump regarding this fascinating line of inquiry.

Modeling parasite transmission – well-mixed or spatially structured?

When we model parasite transmission, we usually assume that the parasite is moving through a population of hosts that is homogeneous and well-mixed.  This is the “mass-action” type model.  The assumption (for a directly transmitted parasite) is that every infected host is equally likely to interact with every susceptible host.  How realistic is this assumption?  Uhhh… probably not realistic at all, actually.

Instead of being well-mixed, interactions within the host population might occur at a local scale, where hosts only interact with their nearest neighbors.  What if we were to model parasite transmission in two different ways:  first under the assumption that the host population is spatially structured with local interactions, and then under the assumption that the host population is homogeneous and well-mixed.  Would the outcomes of the two models be different?

Enter a recent, freaking awesome Am Nat paper by Wodarz et al. (2013), who did just that.  When they used spatially structured vs. mixed populations in an agent based model, they found that host (and thus parasite) extinction was more likely in the spatially structured population.  They saw the same outcome using ODE metapopulation models.  Why should restricting interactions to the local scale increase the risk of extinction?  Wodarz et al. (2013) argue that it is because the carrying capacity at the local scale is smaller than the carrying capacity in the well-mixed model.  (See the self-shading idea, below.)  Basically, a giant chunk of the “population persistence” parameter space in well-mixed models is lost when we switch to spatially structured models.

Figure 3 from Wodarz et al. (2013). Extinction is more likely in populations that are spatially structured than in populations that are well-mixed.

You ought to go take a look at the Wodarz et al. (2013) paper, because it is packed with cool stuff.  Like, what if we change the scale of the local interactions?  What if introduce migration among local neighborhoods (=patches)?  Also, it’s open access.  GO LOOK.

(EDIT:  Begon et al. (2002) argue that you can also have what they call “homogeneous contact experience” without having homogeneous mixing – that is, even when interactions are spatially structured.  If the rates of contact at a local, nearest-neighbor scale are the same as those at the global scale, you still get a homogeneous contact experience.  Wodartz et al. considered both types of spatial structuring – the kind where local interactions scale with global interactions, and the kind where they don’t.)

How do spatially structured host populations affect parasite evolution?

            Evolutionarily speaking, parasites don’t “want” their host population to go extinct.  So, we should expect that there is some evolutionary pressure to maximize parasite transmission while minimizing the probability of host extinction.  (I’ve talked about the tradeoff between transmission and virulence in a previous post.)  In spatially-structured populations, where host (and thus parasite) extinction is more likely, we might therefore expect strong pressures for the evolution of less virulent parasites and/or lower transmission rates.

Boots and Mealor (2007) did an interesting experiment to test the hypothesis that parasites will evolve to have lower transmission rates in more spatially structured host populations.  By interesting, I mean that they put moth larvae (the hosts) in three concentrations of jello – soft, intermediate, and hard.  In the hard jello, moth larvae had the most restricted movement, and thus the most spatially structured populations.  Then they introduced a virus into the moth-jello environment, and tracked the evolution of the virus’ infectivity (which is part of the transmission rate).  As predicted, they found evolution to reduced infectivity/transmission in the hard jello.

When I first read Boots and Mealor (2007), I could not wrap my head around this idea that parasites with high transmission rates would “self-shade” themselves into extinction in highly structured host populations.  The idea is that in spatially structured populations, every infected host individual will be surrounded by other infected individuals if transmission rates are high, so the parasite’s offspring will have no new territory to conquer.  At first, that sounds pretty good for the parasite – it was so successful that it spread to all available hosts!  But if no new susceptible hosts turn up to be infected – either from birth processes or immigration – then the parasite will go extinct.  Enter a cool modeling paper by Lion and Boots (2010).  They show that yes, evolution can select for parasites that are “less harmful” (=lower virulence) and “slower transmitting” (e.g., lower infectivity), but this depends on the rate of demographic turnover in the population.  So. Cool.

References:

Boots, M., and M. Mealor. 2007. Local Interactions Select for Lower Pathogen Infectivity.  Science 315: 1284-1286.

Lion, S., and M. Boots. 2010. Are parasites prudent in space?  Ecology Letters 13: 1245–1255.  (Open access link to paper)

Wodarz, D., Z. Sun, J.W. Lau, and N.L. Komrova.  2013.  Nearest-Neighbor Interactions, Habitat Fragmentation, and the Persistence of Host-Pathogen Systems.  American Naturalist 182(3): E94-E11.  (Link to paper)

Grooming and Parasite Transmission

If you hadn’t guessed yet, I’m really interest in how parasite consumption affects parasite transmission.  One type of parasite consumption that I haven’t talked about yet is grooming.

You’ve probably had some experience with using grooming to reduce parasite transmission if you have kids or if you ever were a kid: the dreaded lice infestation!  One recommendation for reducing lice transmission is to avoid sharing hats and combs and the like – to reduce contact/encounter rates – and another is to use those lovely lice shampoos (=grooming).

Presumably, if you’ve had lice, you didn’t eat them.  (Your loss.)  But, of course, many animals do eat their picked off parasites.  Free food!

Cartoon by Sardonic Salad.

You might be wondering:  when animals groom themselves or each other, does it actually reduce parasite transmission?  The answer is YES, and it can even reduce parasite transmission to YOU.  I’ve written before about how host biodiversity can reduce parasite transmission if communities with low biodiversity tend to have highly competent hosts.  For instance, in the Lyme disease system, white-footed mice are highly competent, resilient hosts, and opossums have low competence, and are less resilient.  But why the difference in their host competence?  Well, one reason is that opossums are really good at grooming themselves and killing ticks, while white-footed mice are not-so-good at grooming.

Ok, so, grooming can reduce parasite transmission.  Does grooming ever increase parasite transmission?  Why YES, sometimes it does!  For instance, female Japanese macaques of high rank are more likely to be infected with nematodes and have higher parasite loads than females of lesser rank (open access!).  While the mechanism is somewhat unclear, the trend appears to be related to the fact that high ranking females are groomed by and groom more individuals than lower ranking females.  (In this case, increasing contact/encounter rates.)  Neat!

I wonder if early humans groomed each other, and if so, when did that allogrooming behavior stop?  Or did it stop?